Aim & Scope

International Conference on Internet of Things and Machine Learning (IML 2017)
Venue: Liverpool John Moores University
October 17 – 18, 2017
Liverpool city, United Kingdom

ACM ICPS v.2B

The International Conference on Internet of Things and Machine Learning (IML 2017) will be held between the 17th and the 18th of October 2017 in the city of Liverpool in the United Kingdom. Through its technical program, the IML 2017 Conference aims to provide an outstanding opportunity for both academic and industrial communities alike to address new trends and challenges, emerging technologies and progress in standards on topics relevant to today’s fast moving areas of Internet of Things and Machine Learning. This conference will discuss new results in the fields of Internet of things and machine learning.

IML 2017 will offer oral, poster sessions, tutorials, and professional meetings. The program of the IML 2017 Conference intends to foster scientific interaction so as to open the way to future cooperation between participants. All researchers and teams who develop research or recently became interested in the domains of Internet of things and machine learning are invited. Submitted papers are expected to cover state-of-the-art technologies, theoretical concepts, standards, products implementation, ongoing research projects, and innovative applications of the Internet of things and machine learning technologies use.

All accepted papers (regular, short, and poster) will be published by ACM – International Conference Proceedings Series (ICPS) and will be available in ACM Digital Library . ISBN: 978-1-4503-5243-7

Authors are invited to submit papers (Abstract, Full Paper, Poster Paper, or Short paper) presenting original research in all areas of Internet of things and machine learning. Original unpublished manuscripts, and not currently under review in another journal or conference, are solicited in relevant areas including, but not limited to:

Internet of Things:

  • Wireless communications
  • Understanding Networks and Networking protocols
  • Sensors and hardware programming
  • Smart Cities (Smart parking, Smartphone detection, Traffic congestion, Smart lighting, etc.).
  • Smart Water (Potable water monitoring, Chemical leakage detection in rivers, River floods, etc.).
  • Security & Emergencies
  • Retail (Supply chain control, Intelligent shopping applications, Smart product management, etc.).
  • Logistics (Quality of shipment conditions, Item location, etc.).
  • Industrial Control (M2M Applications, Indoor air quality, Temperature monitoring, etc.).
  • Smart Agriculture (Green houses)
  • Digital Health-care / Telehealth / Telemedicine
  • Information security
  • Cloud computing
  • IP multimedia subsystems
  • Connectivity
  • Smart Farming
  • Smart Grids

Machine Learning:

  • Statistical Methods
  • Data Engineering (capture, storage, search, sharing, modeling)
  • Advanced Data Computing
  • Visualization
  • Pattern Recognition
  • Data Interpretation and Analysis
  • Data Mining
  • Data Analytics
  • Big Data Challenges
  • Multimedia Learning
  • Multi-Graph Learning
  • Deep Learning
  • Neural Networks
  • Support Vector Machines
  • Evolutionary computations
  • Fuzzy approaches
  • Genetic Algorithms
  • Features Selection
  • Artificial Intelligence
  • Signal and Image Processing
  • Applications of Machine Learning